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Articles tagged with #rag
In the previous section, we saw that Shreya didn鈥檛 get the expected response when she asked: Explain the difference between waveguide and coaxial cable in practical applications. The system returned partial matches or generic definitions鈥攏ot the cr...
In the previous section, we saw that although Shreya made a good improvement in her system and it worked well for a few prompts, it still struggled with complex tasks. In such cases, the LLM was hallucinating and not performing well. Chain of Thought...
In the previous section, we saw that Shreya faced a problem. When she asked a simple question expecting a straightforward answer, she was overwhelmed with too much information and responses she didn't request. To recap, the question was: What was th...
In the last chapter, we saw how Shreya was discouraged by her system's response to one of her questions. She then returned to the drawing board to find ways to improve her system. Let's see what she discovered and whether it solved her issue. Let me ...
Welcome to the first blog of the series RAG鈥擜 powerful technique that enhances the accuracy and relevance of responses generated by large language models (LLMs) by incorporating information from external data sources relevant to user鈥檚 query. 馃挕 Pre...
